Wistar Symposium "Mathematical Challenge to Neo-Darwinism".

In 1966 a group of physicist and engineers made plans to hold a meeting regarding mathematics and evolution. They invited well known biologist from Harvard and MIT. The meeting became known as the "Mathematical Challenge to Neo-Darwinism. The engineers asked their  routine question "does it work" a question that needed to be addressed. I searched the net for some documentations, but I've had little luck.
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THE ORIGINAL WISTAR SYMPOSIUM IN 1966
In 1966 a group of mathematicians and intellectuals met for a series of speeches known collectively as “Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution.” As Casey Luskin described it, “One of the best mathematical forays into evolution was the 1966 Wistar Symposium, held in Philadelphia, where mathematicians and other scientists from related fields congregated to assess whether Neo-Darwinism is mathematically feasible. The conference was chaired by Nobel Laureate Sir Peter Medawar.” - EvolutionNews.org, July 6, 2006.
Peter Medawar said, "[T]he immediate cause of this conference is a pretty widespread sense of dissatisfaction about what has come to be thought of as the accepted evolutionary theory in the English-speaking world, the so-called neo-Darwinian Theory. ... There are objections made by fellow scientists who feel that, in the current theory, something is missing ... These objections to current neo-Darwinian theory are very widely held among biologists generally; and we must on no account, I think, make light of them. The very fact that we are having this conference is evidence that we are not making light of them." - Sir Peter Medawar, "Remarks by the Chairman," Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution, Wistar Institute Press, 1966, No. 5, pg. xi.
Murray Eden, Ph.D. in Chemistry, said, "[A]n opposite way to look at the genotype is as a generative algorithm and not as a blue-print; a sort of carefully spelled out and foolproof recipe for producing a living organism of the right kind if the environment in which it develops is a proper one. Assuming this to be so, the algorithm must be written in some abstract language. Molecular biology may well have provided us with the alphabet of this language, but it is a long step from the alphabet to understanding a language. Nevertheless a language has to have rules, and these are the strongest constraints on the set of possible messages. No currently existing formal language can tolerate random changes in the symbol sequences which express its sentences. Meaning is almost invariably destroyed. Any changes must be syntactically lawful ones. I would conjecture that what one might call 'genetic grammaticality' has a deterministic explanation and does not owe its stability to selection pressure acting on random variation." - Murray Eden, "Inadequacies as a Scientific Theory," Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution, Wistar Institute Press, 1966, No. 5, pg. 11.
Mathematician Stanislaw Ulam said, "[I]t seems to require many thousands, perhaps millions, of successive mutations to produce even the easiest complexity we see in life now. It appears, naively at least, that no matter how large the probability of a single mutation is, should it be even as great as one-half, you would get this probability raised to a millionth power, which is so very close to zero that the chances of such a chain seem to be practically non-existent." - Stanislaw M. Ulam, "How to Formulate Mathematically Problems of Rate of Evolution," Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution, Wistar Institute Press, 1966, No. 5, pg. 21.
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French mathematician and Doctor of Medicine Marcel Schutzenberger said,"We do not know any general principle which would explain how to match blueprints viewed as typographic objects and the things they are supposed to control. The only example we have of such a situation (apart from the evolution of life itself) is the attempt to build self-adapting programs by workers in the field of artificial intelligence. Their experience is quite conclusive to most of the observers: without some built-in matching, nothing interesting can occur. Thus, to conclude, we believe that there is a considerable gap in the neo-Darwinian theory of evolution, and we believe this gap to be of such a nature that it cannot be bridged within the current conception of biology." - Marcel Schutzenberger, "Algorithms and Neo-Darwinian Theory," Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution, Wistar Institute Press, 1966, No. 5, pg. 75.
http://www.3dmisc.com/Science2016/originalsymposium.htm
How the biologist responded to these "problems"? I've found nothing on the net. I found a book on Amazon for $300, but I'm not buying it. This symposium took place in 1966, so it's possible that the
challenges have been met in the intervening years since then. However, I know of several challenges that so far as I know have not been answered.
The questions  are: There are over 500 amino acids found in nature, 50% left-handed, but if blind, aimless, unguided natural processes selected the 20 or 22 amino acids that used by all life what are
the chances of these particular particular 20 left-handed amino acids being selected?  I realize there are theories offered to explain why only left-handed amino acids were selected, but what about the 20? Or is it possible that any other set of amino acids would have worked just as well?
Of course, the chain of amino acids express precisely the order or linage  that form proteins and the way they are folded. This only pushes the problem back. This raises the question of chance. There are 300-440 average numbers of amino acids that spell out the protein. What's the chance that unguided and random processes would have hit upon the right sequence in the linkage of acids. So, a chain of  just 150, is worked out there is 1 chance out of 10^164.
https://www.str.org/w/building-a-protein-by-chance
In a universe where blind, unguided, aimless random the odds are very long. No one would bet his life on such long odds? And maybe some would.
In spite of these long odds, there are many different proteins in a living organism. So, this is where instructions has to play fundamental role. This is where DNA comes is which is "know how", instructions information. In the real world when ever you trace this information back to it's source, It always goes back to an engineer or other intelligence.